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5?mm?��?1.5?mm?��?2?mm. Parallel imaging (GRAPPA) was used to enable short TE required in ultra-high field fMRI. Acquired fMRI data were pre-processed and analyzed in SPM8 (FIL this website Group, UC London, UK). Preprocessing included correction for slice-timing differences [18], realignment to compensate for bulk head motion, normalization to standard MNI space using an in-house developed EPI template optimized for 7?T EPI imaging. Data were spatially smoothed with an isotropic Gaussian kernel of 8?mm FWHM to reduce the impact of individual anatomical differences in random-effects group analysis and account for the spatial distribution of the BOLD effect. The estimated size of our target regions, particularly the amygdala, was the rationale for the size of the smoothing kernel. First-level single-subject analysis was conducted using the general linear model (GLM) framework implemented in SPM8. Two boxcar functions of the onsets and durations of the two task conditions were convolved with SPM8's canonical hemodynamic response function. These two separate regressors were designed to model changes in hemodynamic responses during emotional face discrimination and object discrimination. Further, six realignment parameters obtained from SPM8's motion correction algorithm. Time courses from white-matter regions and ventricles were also included in the design matrix to reduce motion and physiological artifacts. Second-level INSRR group analysis was performed by conducting a one-sample t-test on the individuals�� BLZ945 contrasts between emotion and object discrimination (i.e. EDT?>?ODT). Significance threshold was set to p?